Conventionally, when a text is converted into voices, a translation work has been efficiently performed using transliteration support devices. Specifically, when editing a text serving as a voice synthesis target, the conventional transliteration support device first performs morpheme analysis and produces phonetic character strings for each of the texts before and after editing. The conventional transliteration support device, then, determines whether the text is edited for modifying readings or accents of the synthesized voices on the basis of the morpheme analysis result.
When it is determined that the text is edited for modifying readings or accents of the synthesized voices, the conventional transliteration support device produces editing history data indicating the editing content and stores it in a storage unit. When an error in voice is pointed out by an operator, the conventional transliteration support device searches the editing history data for the editing content of the text editing that should be performed for the modification. When the editing content has been found, the conventional transliteration support device automatically re-edits the text.
In the conventional transliteration support technology, the text that is the same as the text modified in the past, which is indicated by the editing history data stored in the storage unit, is the target of the modification. The conventional transliteration support device, thus, needs to repeat the modification of similar readings, accents, pausing positions, or voice synthesis parameters. As a result, a problem arises in that it is difficult to efficiently perform transliteration work.